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Discovering regulatory motifs in the Plasmodium genome using comparative genomics Export

Bioinformatics (Oxford, England) In Bioinformatics, Vol. 24, No. 17. (1 September 2008), pp. 1843-1849.

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comparative genomics malaria

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Motivation: Understanding gene regulation in Plasmodium, the causative agent of malaria, is an important step in deciphering its complex life cycle as well as leading to possible new targets for therapeutic applications. Very little is known about gene regulation in Plasmodium, and in particular, few regulatory elements have been identified. Such discovery has been significantly hampered by the high A-T content of some of the genomes of Plasmodium species, as well as the challenge in associating discovered regulatory elements to gene regulatory cascades due to Plasmodium's complex life cycle. Results: We report a new method of using comparative genomics to systematically discover motifs in Plasmodium without requiring any functional data. Different from previous methods, our method does not depend on sequence alignments, and thus is particularly suitable for highly divergent genomes. We applied our method to discovering regulatory motifs between the human parasite, P.falciparum, and its rodent-infectious relative, P.yoelii. We also tested our procedure against comparisons between P.falciparum and the primate-infectious, P.knowlesi. Our computational effort leads to an initial catalog of 38 distinct motifs, corresponding to over 16 200 sites in the Plasmodium genome. The functionality of these motifs was further supported by their defined distribution within the genome as well as a correlation with gene expression patterns. This initial map provides a systematic view of gene regulation in Plasmodium, which can be refined as additional genomes become available. Availability: The new algorithm, named motif discovery using orthologous sequences (MDOS), is available at http://www.ics.uci.edu/[~]xhx/project/mdos/. Contact: xhx@ics.uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btn348


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